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• Collect, clean, and preprocess data from various sources, such as databases, APIs, web scraping, or surveys
• Explore and analyze data to discover patterns, trends, and anomalies, and generate hypotheses and questions
• Build and test predictive models and machine learning algorithms, using tools such as TensorFlow, PyTorch, or Scikit-learn
• Evaluate and optimize the performance and accuracy of the models and algorithms, and fine‑tune the parameters and features
• Deploy and integrate the models and algorithms into production systems and applications, using tools such as Flask, Docker, or Kubernetes
• Create and deliver data products and solutions, such as dashboards, reports, and visualizations, using tools such as Plotly, D3.js, or Shiny
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